Prognostic models discriminate between groups of individuals likely to experience better or worse outcomes and to predict response to treatment.

The premise of the analysis was the assumption that baseline PANSS measurements could be a prognostic factor to inform decisions on the expected response (completion or early-termination) to treatment during participation in a clinical trial.

To examine early patterns/profiles based on PANSS and response to treatment (Study-Completer (SC), Early-Termination (ET)).

Receiver Operating Curves (ROC) was conducted on 809 subjects with SC versus ET. Factor structure assessed whether psychopathology constructs are comparable across SC and ET.

Positive-Symptoms: P5.Grandiosity, P7.Hostility and P4.Excitement are not as good as others in predicting ET. 91.1% ET would have scores of 5, 6 or 7 on P1.Delusions.

Negative-Symptoms: N5. Difficulty in Abstract Thinking and N6.Lack of Spontaneity and Flow of Conversation are not as good in predicting ET. 67.9% ET may have scores of 5, 6 or 7 on N1.Blunted Affect. General-Psychopathology: G3.Guilt Feelings, G6.Depression, G7.Motor Retardation, and G10.Disorientation are not as good in predicting ET. 73.2% ET have scores of 5, 6 or 7 on G9.Unusual Thought Content. Positive Factor accounted for the most variance 15.885%, then Negative factor=14.592%, then Hostile-Excitement=11.973% for SC. For ET, Negative Factor=13.713% variance, cognitive factor=12.451%, Excitement Factor=10.396%.

These findings represent patterns of early detection of response in clinical trials, and have led to the development of sophisticated algorithms that may allow investigators to identify ET and SC, which is important in trial success.